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ICCV
2007
IEEE

Joint Affinity Propagation for Multiple View Segmentation

10 years 4 months ago
Joint Affinity Propagation for Multiple View Segmentation
A joint segmentation is a simultaneous segmentation of registered 2D images and 3D points reconstructed from the multiple view images. It is fundamental in structuring the data for subsequent modeling applications. In this paper, we treat this joint segmentation as a weighted graph labeling problem. First, we construct a 3D graph for the joint 3D and 2D points using a joint similarity measure. Then, we propose a hierarchical sparse affinity propagation algorithm to automatically and jointly segment 2D images and group 3D points. Third, a semi-supervised affinity propagation algorithm is proposed to refine the automatic results with the user assistance. Finally, intensive experiments demonstrate the effectiveness of the proposed approaches.
Jianxiong Xiao, Jingdong Wang, Ping Tan, Long Quan
Added 14 Oct 2009
Updated 30 Oct 2009
Type Conference
Year 2007
Where ICCV
Authors Jianxiong Xiao, Jingdong Wang, Ping Tan, Long Quan
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